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Hu everyone,
I am trying to script the ensemble, however, argsvar cannot be used with torchscript
torch.jit.frontend.NotSupportedError: Compiled functions can't take variable number of argument…
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getting started with a wishlist for outlier robust multivariate location and scatter estimators
#3220 size (overall scaling)
- MCD in scikit-learn, not good with high contamination and large k_vars
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Instead of asking the user to download the LD matrices every time they need to run, e.g. `viprs`, we can leverage Zarr's APIs for cloud storage and read the matrices from a central repository on, e.g.…
shz9 updated
2 months ago
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For gene ranking (for GSEA, for example) and visualizations (on volcano plots, for example), DESeq author Michael Love suggests shrinking of the effect sizes (log-fold changes) with the `lfcShrink` fu…
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A few comments/questions
1. The structs `Simple`, `Uncorrected` are a bit useless, would it maybe make sense to have something that's closer to the initial `cov` call such as:
```julia
cov(X, c…
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(issue mainly to park an article that might have good general theory in MLE context, not read yet)
related PR #1665 TheilGLS, generalized Ridge for linear model
Hansen, Bruce E. 2016. “Efficient Shr…
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Hello - thanks all for the very interesting looking package. The hierarchical shrinkage wrapper seems especially interesting/novel. I'm interested in whether it would be possible to add sample weight …
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(mainly parking a reference for an old idea)
variance and covariance estimates are not very good in small or very small samples.
One idea is to use penalized or shrinkage (co)variance to get bette…
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Hi @Marigold,
You suggested to implement Ledoit-Wolf covariance estimation at the end of [modern-portfolio-theory.ipynb](https://github.com/Marigold/universal-portfolios/blob/master/modern-portfoli…
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shrinking the endog is another principle that allows reuse of existing methods for robust regression. This is similar to winsorizing and an alternative to trimming or dropping outliers (e.g. #3273 #9…